Using Implied Probabilities to Improve the Estimation of Unconditional Moment Restrictions for Weakly Dependent Data

Using the seminal contributions of Bonnal and Renault (2001) and Antoine et al. (2007), we propose two three-step Euclidian empirical likelihood (3S-EEL) estimators for weakly dependent data. Both estimators make use of a control variates principle that can be interpreted in terms of implied probabilities in order to achieve higher-order improvements relative to the traditional two-step GMM estimator.

A Monte Carlo study reveals that the finite and large sample properties of the three-step estimators compare favorably to the existing approaches: the two-step GMM and the continuous updating estimator.